1 | partial differential equation | PDE | 270 | 25 | 1.00318 | 2009.00139,2009.00736,etc |
2 | theorem | Theorem | 888 | 23 | 2.00238 | 2009.00177,2009.00233,etc |
3 | channel state information | CSI | 244 | 19 | 2.004503 | 2009.00105,2009.00171,etc |
4 | signal to noise ratio | SNR | 129 | 19 | 2.001503 | 2009.00105,2009.00517,etc |
5 | deutsche forschungsgemeinschaft | DFG | 19 | 18 | 1.000218 | 2009.00316,2009.00352,etc |
6 | base station | BS | 478 | 16 | 2.00373 | 2009.00105,2009.00267,etc |
7 | multiple input multiple output | MIMO | 161 | 14 | 2.002127 | 2009.00389,2009.00724,etc |
8 | line of sight | LoS | 212 | 14 | 2.003192 | 2009.00473,2009.01988,etc |
9 | additive white gaussian noise | AWGN | 29 | 13 | 1.000725 | 2009.00267,2009.00806,etc |
10 | stochastic differential equation | SDE | 198 | 13 | 1.001744 | 2009.01276,2009.01299,etc |
11 | internet of things | IoT | 128 | 11 | 1.004284 | 2009.00105,2009.00724,etc |
12 | european research council | ERC | 15 | 11 | 1.00021 | 2009.00441,2009.01201,etc |
13 | alternating direction method of multipliers | ADMM | 330 | 11 | 2.004408 | 2009.00801,2009.01790,etc |
14 | ordinary differential equation | ODE | 109 | 10 | 2.001575 | 2009.01299,2009.02327,etc |
15 | karush kuhn tucker | KKT | 81 | 10 | 2.002396 | 2009.03020,2009.03880,etc |
16 | intelligent reflecting surface | IRS | 861 | 9 | 2.007701 | 2009.00267,2009.02324,etc |
17 | finite element method | FEM | 81 | 9 | 1.002248 | 2009.00532,2009.00571,etc |
18 | signal to interference plus noise ratio | SINR | 264 | 9 | 1.006348 | 2009.00724,2009.01753,etc |
19 | mean squared error | MSE | 37 | 9 | 1.000405 | 2009.00801,2009.02327,etc |
20 | radio frequency | RF | 95 | 8 | 2.004244 | 2009.00328,2009.00789,etc |
21 | reconfigurable intelligent surface | RIS | 406 | 8 | 2.008737 | 2009.00517,2009.00789,etc |
22 | discontinuous galerkin | DG | 278 | 8 | 2.00462 | 2009.00704,2009.00991,etc |
23 | model predictive control | MPC | 192 | 8 | 2.005097 | 2009.01298,2009.01332,etc |
24 | lemma | Lemma | 406 | 8 | 2.001496 | 2009.02644,2009.03127,etc |
25 | singular value decomposition | SVD | 74 | 7 | 2.001689 | 2009.00267,2009.00389,etc |
26 | probability density function | PDF | 23 | 7 | 2.000793 | 2009.00328,2009.00517,etc |
27 | maximum likelihood | ML | 65 | 7 | 2.003481 | 2009.00789,2009.02507,etc |
28 | kullback leibler | KL | 81 | 7 | 2.002206 | 2009.01364,2009.01704,etc |
29 | millimeter wave | mmWave | 156 | 7 | 2.002289 | 2009.01988,2009.02747,etc |
30 | non orthogonal multiple access | NOMA | 243 | 6 | 1.008928 | 2009.00105,2009.00267,etc |
31 | proper orthogonal decomposition | POD | 32 | 6 | 2.00081 | 2009.01332,2009.01596,etc |
32 | minimum mean square error | MMSE | 116 | 6 | 1.003808 | 2009.02031,2009.02747,etc |
33 | optimal control problem | OCP | 46 | 6 | 1.002575 | 2009.04187,2009.05686,etc |
34 | markov chain monte carlo | MCMC | 29 | 5 | 1.000383 | 2009.00195,2009.04239,etc |
35 | eavesdropper | Eve | 294 | 5 | 2.00413 | 2009.00517,2009.05920,etc |
36 | bit error rate | BER | 39 | 5 | 1.000838 | 2009.00789,2009.00806,etc |
37 | orthogonal frequency division multiplexing | OFDM | 22 | 5 | 2.000559 | 2009.00806,2009.02747,etc |
38 | hamilton jacobi bellman | HJB | 41 | 5 | 2.00111 | 2009.01332,2009.05667,etc |
39 | algorithm | Algorithm | 87 | 5 | 2.000938 | 2009.01349,2009.02911,etc |
40 | fifth generation | 5G | 41 | 5 | 2.002904 | 2009.02324,2009.06286,etc |
41 | convolutional neural network | CNN | 29 | 5 | 1.001809 | 2009.02713,2009.04103,etc |
42 | user equipment | UE | 181 | 5 | 2.005323 | 2009.02747,2009.02875,etc |
43 | mean square error | MSE | 109 | 5 | 2.004394 | 2009.02747,2009.03892,etc |
44 | central limit theorem | CLT | 25 | 5 | 1.002729 | 2009.03000,2009.05420,etc |
45 | maximum a posteriori | MAP | 116 | 5 | 2.002388 | 2009.03504,2009.04188,etc |
46 | reproducing kernel hilbert space | RKHS | 28 | 5 | 1.001046 | 2009.04188,2009.04239,etc |
47 | orthogonal multiple access | OMA | 129 | 4 | 2.006584 | 2009.00105,2009.00267,etc |
48 | artificial noise | AN | 55 | 4 | 2.00153 | 2009.00267,2009.00473,etc |
49 | electrical impedance tomography | EIT | 19 | 4 | 2.000943 | 2009.00370,2009.02525,etc |
50 | semidefinite relaxation | SDR | 36 | 4 | 1.000892 | 2009.00473,2009.02747,etc |
51 | gradient descent | GD | 53 | 4 | 1.001616 | 2009.00673,2009.02604,etc |
52 | total variation | TV | 66 | 4 | 2.005922 | 2009.00801,2009.03470,etc |
53 | stochastic gradient descent | SGD | 40 | 4 | 1.002409 | 2009.01790,2009.02713,etc |
54 | linear program | LP | 48 | 4 | 2.00072 | 2009.01942,2009.02377,etc |
55 | unmanned aerial vehicle | UAV | 10 | 4 | 1.000136 | 2009.01988,2009.02716,etc |
56 | markov decision process | MDP | 13 | 4 | 1.000199 | 2009.02053,2009.02146,etc |
57 | reduced order model | ROM | 101 | 4 | 1.00449 | 2009.02176,2009.02769,etc |
58 | multiple access channel | MAC | 51 | 4 | 1.001585 | 2009.02324,2009.03788,etc |
59 | conjugate gradient | CG | 80 | 4 | 1.003038 | 2009.02604,2009.05814,etc |
60 | expectation maximization | EM | 5 | 4 | 1.000229 | 2009.02736,2009.05072,etc |
61 | uniform linear array | ULA | 11 | 4 | 1.00081 | 2009.02747,2009.03528,etc |
62 | reinforcement learning | RL | 35 | 4 | 2.002706 | 2009.02911,2009.03616,etc |
63 | angle of arrival | AoA | 62 | 4 | 1.002405 | 2009.03536,2009.05893,etc |
64 | discrete fourier transform | DFT | 14 | 4 | 1.00075 | 2009.03536,2009.04428,etc |
65 | stochastic partial differential equation | SPDE | 15 | 4 | 2.000187 | 2009.05421,2009.06137,etc |
66 | quality of service | QoS | 21 | 3 | 1.000783 | 2009.00105,2009.00267,etc |
67 | successive interference cancellation | SIC | 17 | 3 | 1.000647 | 2009.00105,2009.00267,etc |
68 | upper confidence bound | UCB | 15 | 3 | 2.000779 | 2009.00105,2009.01339,etc |
69 | conjecture | Conjecture | 16 | 3 | 2.000261 | 2009.00233,2009.01831,etc |
70 | physical layer security | PLS | 41 | 3 | 2.000597 | 2009.00267,2009.01988,etc |
71 | successive convex approximation | SCA | 10 | 3 | 2.000639 | 2009.00473,2009.05893,etc |
72 | batalin vilkovisky | BV | 166 | 3 | 2.002013 | 2009.00509,2009.04064,etc |
73 | science and engineering research board | SERB | 3 | 3 | 1.000049 | 2009.00532,2009.00571,etc |
74 | linear matrix inequality | LMI | 22 | 3 | 1.000644 | 2009.00673,2009.05893,etc |
75 | circularly symmetric complex gaussian | CSCG | 5 | 3 | 1.000173 | 2009.00724,2009.02551,etc |
76 | linear time invariant | LTI | 24 | 3 | 1.001346 | 2009.00739,2009.02468,etc |
77 | positive intrinsic negative | PIN | 9 | 3 | 1.000131 | 2009.00789,2009.02694,etc |
78 | definition of | Definition | 30 | 3 | 2.000431 | 2009.01124,2009.07953,etc |
79 | linear programming | LP | 81 | 3 | 2.0019 | 2009.01298,2009.02377,etc |
80 | partial integro differential equation | PIDE | 27 | 3 | 2.000407 | 2009.01392,2009.06521,etc |
81 | isogeometric analysis | IGA | 239 | 3 | 2.00963 | 2009.01499,2009.08132,etc |
82 | virtual reality | VR | 71 | 3 | 1.003332 | 2009.01632,2009.01753,etc |
83 | difference of convex | DC | 10 | 3 | 1.000485 | 2009.01753,2009.03504,etc |
84 | maximum ratio transmission | MRT | 12 | 3 | 1.00042 | 2009.01753,2009.02875,etc |
85 | section | Section | 27 | 3 | 2.000354 | 2009.01988,2009.06563,etc |
86 | non line of sight | NLoS | 52 | 3 | 2.001265 | 2009.01988,2009.03536,etc |
87 | poisson point process | PPP | 5 | 3 | 1.000154 | 2009.02031,2009.02192,etc |
88 | nash equilibrium | NE | 16 | 3 | 1.000654 | 2009.02053,2009.02146,etc |
89 | broadcast channel | BC | 95 | 3 | 2.002912 | 2009.02324,2009.04010,etc |
90 | left hand side | LHS | 4 | 3 | 1.000296 | 2009.02324,2009.04564,etc |
91 | raviart thomas | RT | 4 | 3 | 1.00042 | 2009.02607,2009.03928,etc |
92 | pairwise error probability | PEP | 26 | 3 | 2.000749 | 2009.02682,2009.03536,etc |
93 | electromagnetic | EM | 35 | 3 | 2.002166 | 2009.02694,2009.08038,etc |
94 | deep neural network | DNN | 74 | 3 | 1.002857 | 2009.02713,2009.08024,etc |
95 | angle of departure | AoD | 54 | 3 | 1.002811 | 2009.03536,2009.05893,etc |
96 | log likelihood ratio | LLR | 57 | 3 | 2.001737 | 2009.04148,2009.05072,etc |
97 | cyclic redundancy check | CRC | 29 | 3 | 2.001882 | 2009.04338,2009.06796,etc |
98 | maximum likelihood estimator | MLE | 6 | 3 | 1.000064 | 2009.04856,2009.08562,etc |
99 | nonlinear schr"odinger | NLS | 15 | 3 | 2.000237 | 2009.04929,2009.06877,etc |
100 | nonlinear programming | NLP | 14 | 3 | 2.001865 | 2009.05845,2009.05873,etc |